Boost your Big Data skills by working on
Hadoop Projects designed by industry experts

In this project, we are going to analyze streaming logfile dataset by integrating Kafka and Kylin.

In this project, we will talk about Apache Zeppelin. We will write code, write notes, build charts and share all in one single data analytics environment using Hive, Spark and Pig.

In this project, we will be performing an OLAP cube design using the AdventureWorks dataset. The deliverable for this session will be to design a cube, build and implement it using Kylin, query the cube and even connect familiar tools (like Excel) with our new cube.

In this project, we will use the yelp review dataset to analyze businesses, reviews and ingest the final output of our data processing in Elasticsearch and use the visualization tool in the ELK stack to visualize various kinds of ad-hoc reports from the data.

In this project, we will look at how to mine and make sense of connections in a simple way by building a Spark GraphX Algorithm and a Network Crawler.

In this project, we will simulate a simple real-world batch data pipeline based on messaging using Spark and Hive.

In this big data project, we will see how data ingestion and loading is done with Kafka connect APIs while transformation will be done with Kafka Streaming API.

Hive Project- Understand the various types of SCDs and implement these slowly changing dimesnsion in Hadoop Hive and Spark.

It is continuation of the previous hackerday "Tough engineering choices with large datasets in Hive Part - 1", where we will work on processing big data sets using Hive.

Learn to design Hadoop Architecture and understand how to store data using data acquisition tools in Hadoop.

Learn to write a Hadoop Hive Program for real-time querying.

Towards mastery in Hive in processing big datasets.

Hive Project -Learn to write a Hive program to find the first unique URL, given 'n' number of URL's.

In this hackerday, we will explore the features of Spark SQL in practice.

In this hackerday, we will be performing a real time processing of log entries from applications, using Kafka for the streaming architecture in a microservice sense.

In this hackerday, we are going to bring processing to the speed layer of the lambda architecture which opens up capabilities to monitor application real time performance, measure real time comfort with applications and real time alert in case of security

In this hadoop project, learn about the features in Hive that allow us to perform analytical queries over large datasets.

In this project, our goal is to build an argument for generalized streaming architecture for reactive data ingestion based on a microservice architecture. 

In this project, we want to measure by how much NFP has triggered moves in past markets.

In this project, we will use two NoSQL databases(HBase and MongoDB) to store Yelp business attributes and also learn how to retrieve these data for processing or query.

In this project, we are going to do network analysis using a graph database so that we can find patterns in how a social network affects business reviews and ratings.

In this project, we going to continue building the data warehouse and will do further data processing to deliver different kinds of data products.

In this big data project, we will continue from a previous hive project "Data engineering on Yelp Datasets using Hadoop tools" and do the entire data processing using spark.

PySpark Project-Get a handle on using Python with Spark through this hands-on data processing spark python tutorial.

In this big data project, we will embark on real-time data collection and aggregation from a simulated real-time system using Spark Streaming.

In this Apache Spark SQL project, we will go through provisioning data for retrieval using Spark SQL.

In this big data spark project, we will do Twitter sentiment analysis using spark streaming on the incoming streaming data.

In this project, we are going to be continuing the series on data engineering by discussing and implementing various ways to solve the Hadoop Big Data problem.

In this hive project, you will design a data warehouse for e-commerce environments.

Spark Project - Discuss real-time monitoring of taxis in a city. The real-time data streaming will be simulated using Flume. The ingestion will be done using Spark Streaming.

In this project, we are going to make big data available and accessible.

In this project, we will be applying some data engineering principles to the Yelp Dataset in the areas of processing, storage, and retrieval.

In this project, we are going to build the backend of a IT job ad website.

In this hadoop project, you will be using a sample application log file from an application server to a demonstrated scaled-down server log processing pipeline.

In this project, we will be doing an analysis of the level and strength of interactions across areas of coverage of a telecom provider between different areas in the city of Milan.

In this hive project , we will build a Hive data warehouse from a raw dataset stored in HDFS and present the data in a relational structure so that querying the data will be natural.

In this project, we'll work with Apache Airflow and write scheduled workflow, which will download data from Wikipedia archives, upload to S3, process them in HIVE and finally analyze on Zeppelin Notebooks.

In this project, we will be working on Hive and HQL to analyze movie ratings using MovieLens data for better movie recommendation.

Hadoop Projects for Beginners -Learn data ingestion from a source using Apache Flume and Kafka to make a real-time decision on incoming data.

In this challenge, we will discover songs for those artists that are associated with the culture of different countries.

In this hive project, you will work on denormalizing the JSON data and create HIVE scripts with ORC file format.

Analyze clickstream data of a website using Hadoop Hive to increase sales by optimizing every aspect of the customer experience on the website from the first mouse click to the last.

Use the Hadoop ecosystem to glean valuable insights from the Yelp dataset. You will be analyzing the different patterns that can be found in the Yelp data set, to come up with various approaches in solving a business problem.